Multi-Objective White Shark Optimizer for Global Optimization and Rural Sports-Facilities Location Problem

A swarm intelligence optimization algorithm called white shark optimizer (WSO) has been proposed and successfully applied in regard to many aspects. In this paper, the location problem of sports facilities is regarded as a multi-objective problem, and the number of residents covered by sports facilities and the Weber problem are introduced as objective functions. A multi-objective white shark optimizer (MOWSO) is proposed, and MOWSO introduced an archived mechanism to store the non-dominated solutions obtained by the algorithm. When the Pareto solutions in the archive overflow, the solutions are removed by calculating the true distance of the Pareto optimal solution. The performance of the MOWSO is verified on CEC 2020 benchmark functions, and the results show that the proposed MOWSO is better than other algorithms in the diversity and distribution of solutions. The MOWSO is applied to solve the rural sports facilities location problem, and a variety of different sports facilities location schemes are obtained. It can provide a variety of options for the location of rural sports facilities, and promote the intelligent design of sports facilities.

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Publication Details

Journal
Biomimetics
Published
2025-08-15
DOI
https://doi.org/10.3390/biomimetics10080537
Primary Topic
Urban Transport and Accessibility
Type
article
Field-Weighted Citation Impact
0.00

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article

Multi-Objective White Shark Optimizer for Global Optimization and Rural Sports-Facilities Location Problem

Yongquan Zhou, Bin Guo, Yan Zheng
Biomimetics
Urban Transport and Accessibility
article

Multi-Objective White Shark Optimizer for Global Optimization and Rural Sports-Facilities Location Problem

Yongquan Zhou, Bin Guo, Yan Zheng
article en

Abstract

A swarm intelligence optimization algorithm called white shark optimizer (WSO) has been proposed and successfully applied in regard to many aspects. In this paper, the location problem of sports facilities is regarded as a multi-objective problem, and the number of residents covered by sports facilities and the Weber problem are introduced as objective functions. A multi-objective white shark optimizer (MOWSO) is proposed, and MOWSO introduced an archived mechanism to store the non-dominated solutions obtained by the algorithm. When the Pareto solutions in the archive overflow, the solutions are removed by calculating the true distance of the Pareto optimal solution. The performance of the MOWSO is verified on CEC 2020 benchmark functions, and the results show that the proposed MOWSO is better than other algorithms in the diversity and distribution of solutions. The MOWSO is applied to solve the rural sports facilities location problem, and a variety of different sports facilities location schemes are obtained. It can provide a variety of options for the location of rural sports facilities, and promote the intelligent design of sports facilities.

BiomimeticsVol. 10(8)
Minzu University of China (CN), China University of Political Science and Law (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 78%
Urban Transport and Accessibility
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Multi-Objective White Shark Optimizer for Global Optimization and Rural Sports-Facilities Location Problem — Yongquan Zhou, Bin Guo, et al. · Biomimetics (2025) | TGRS Research Map | TGRS